# Copyright 2019 Google LLC
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from keras.preprocessing.image import ImageDataGenerator

x_train and y_train assume the image data and labels have been resized for the 
# CNN and split into training and test data, but the data has not been normalized.

# instantiate an Image Data generator object
datagen = ImageDataGenerator(rescale=1./255, validation_split=0.1)

# the number of epochs (training passes over the entire training data)
epochs = 10

for epoch in range(epochs):
    # Use generator to create batches
    model.fit_generator(datagen.flow(x_data, y_data, batch_size=32, shuffle=True))
